Modelling Urban Bus Service and Passenger Reliability.

Reliability of public transport systems has been considered critically important by public transport users, operators and the government. Lack of reliability in public transport results in uncertainty and delays aggravating anxiety and discomfort for the passengers and increases costs due to lost mileage and lower fleet utilisation for the operators. The government emphasises a reliable bus-service in order to ensure its competitiveness to car use such that it results in modal shift. Though reliability is of significance to a range of actors such as the bus operators and the passengers, its interpretations vary across different groups. For example, quality of service identified by the demand-oriented indicators, the travellers, is systematically different from what the supply-based quality indicators show. Reliability, as a measure of quality of service, is related to the operational characteristics of the public transport system. Passenger’s wait time, on the other hand, is much more sensitive to schedule reliability than to service frequency. This paper investigates some of the measures used to assess reliability of an urban bus network using a dynamic microsimulation model framework. The framework incorporates models of bus operation, passenger arrival and boarding for buses within a network model of general traffic. It therefore allows explicit modelling of the interactions among cars, buses and passengers and of their effect on bus reliability. The model framework is applied to a case study based on a bus route in the city of York. Empirical analysis of the test route was carried out to understand the background of reliability issues and to establish a sound base scenario of the network. The simulation model is used to help understand the causes and process of occurrence of unreliability and to study the impacts of possible scenarios such as increased congestion, rise in passenger demand, and reduction in ‘per passenger boarding time’ on the reliability of the test-route. The study measures reliability in terms of travel time, headways and excess passenger wait time, and sheds light on factors affecting them. The results of the study reveal that excess passenger wait time is strongly correlated with the variation of headways and an increase in passenger demand intensifies the ‘bunching and spreading out’ of buses. With increasing congestion and passenger demand, reliability is reduced. Reduction in per passenger boarding time proves to be an effective measure in improving reliability. Beyond these specific case study results, the modelling framework developed may serve as a useful tool to assess reliability levels for a future year and to evaluate proposed strategies to improve reliability before implementation. Such a modelling framework, if extended to cover larger bus networks can serve as an important decision-making tool in the hands of the government and bus operators for offering more reliable bus services to the public.